Efficient Computation Offloading for Mobile Edge Computing by Using Success-History based Adaptive DE

As an emerging technique, mobile edge computing (MEC) extends the resource-constrained mobile devices to offload the computation tasks to the edge servers. In this paper, both the edge MEC servers and the center Cloud servers are optional for the computation tasks offloading. Then the computation task offload problem is optimized by the improved success-history based adaptive differential evolution (SHADE) algorithm. Simulation experiments demonstrate that the proposed scheme can effectively reduce the time consumption and the energy consumption of the computation tasks.